Non-Coding RNA最新文献

{"title":"Decoding Salivary ncRNAomes as Novel Biomarkers for Oral Cancer Detection and Prognosis.","authors":"Subhadeep Das, Sampad Basak, Soumyadev Sarkar","doi":"10.3390/ncrna11020028","DOIUrl":"10.3390/ncrna11020028","url":null,"abstract":"<p><p>Oral cancer (OC) ranks among the most prevalent head and neck cancers, becoming the eleventh most common cancer worldwide with ~350,000 new cases and 177,000 fatalities annually. The rising trend in the occurrence of OC among young individuals and women who do not have tobacco habits is escalating rapidly. Surgical procedures, radiation therapy, and chemotherapy are among the most prevalent treatment options for oral cancer. To achieve better therapy and an early detection of the cancer, it is essential to understand the disease's etiology at the molecular level. Saliva, the most prevalent body fluid obtained non-invasively, holds a collection of distinct non-coding RNA pools (ncRNAomes) that can be assessed as biomarkers for identifying oral cancer. Non-coding signatures, which are transcripts lacking a protein-coding function, have been identified as significant in the progression of various cancers, including oral cancer. This review aims to examine the role of various salivary ncRNAs (microRNA, circular RNA, and lncRNA) associated with disease progression and to explore their functions as potential biomarkers for early disease identification to ensure better survival outcomes for oral cancer patients.</p>","PeriodicalId":19271,"journal":{"name":"Non-Coding RNA","volume":"11 2","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11932315/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of Non-Coding RNAs in MYC-Mediated Metabolic Regulation: Feedback Loops and Interactions.","authors":"Aliaa Amr Alamoudi","doi":"10.3390/ncrna11020027","DOIUrl":"10.3390/ncrna11020027","url":null,"abstract":"<p><p>Metabolic reprogramming is a hallmark of cancer, crucial for supporting the rapid energy demands of tumor cells. MYC, often deregulated and overexpressed, is a key driver of this shift, promoting the Warburg effect by enhancing glycolysis. However, there remains a gap in understanding the mechanisms and factors influencing MYC's metabolic roles. Recently, non-coding RNAs (ncRNAs) have emerged as important modulators of MYC functions. This review focuses on ncRNAs that regulate MYC-driven metabolism, particularly the Warburg effect. The review categorizes these ncRNAs into three main groups based on their interaction with MYC and examines the mechanisms behind these interactions. Additionally, we explore how different types of ncRNAs may collaborate or influence each other's roles in MYC regulation and metabolic function, aiming to identify biomarkers and synthetic lethality targets to disrupt MYC-driven metabolic reprogramming in cancer. Finaly, the review highlights the clinical implications of these ncRNAs, providing an up-to-date summary of their potential roles in cancer prognosis and therapy. With the recent advances in MYC-targeted therapy reaching clinical trials, the exciting potential of combining these therapies with ncRNA-based strategies holds great promise for enhancing treatment efficacy.</p>","PeriodicalId":19271,"journal":{"name":"Non-Coding RNA","volume":"11 2","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11932256/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A miRNA Signature for Non-Invasive Colorectal Cancer Diagnosis in Morocco: miR-21, miR-29a and miR-92a.","authors":"Sofia Fathi, Oussama Aazzane, Salma Guendaoui, Nezha Tawfiq, Souha Sahraoui, Fadila Guessous, Mehdi Karkouri","doi":"10.3390/ncrna11020026","DOIUrl":"10.3390/ncrna11020026","url":null,"abstract":"<p><p>Colorectal cancer (CRC) is the third most diagnosed cancer and a leading cause of cancer-related mortality in Morocco, often detected at late stages. Circulating microRNAs (miRNAs) have emerged as promising non-invasive biomarkers for CRC detection, with miR-21, miR-29a, and miR-92a showing significant diagnostic potential. This study aimed to evaluate the expression levels of these miRNAs in a Moroccan population and their efficacy as diagnostic biomarkers.</p><p><strong>Methods: </strong>A prospective study was conducted using blood samples from 50 CRC patients and 50 healthy controls. Circulating miRNA expression levels were quantified through reverse transcription quantitative PCR (RT-qPCR), with normalization to miR-1228-3p. Statistical analyses, including the Mann-Whitney U test, Receiver Operating Characteristic (ROC) curve analysis, sensitivity (Sen), and specificity (Spe) evaluations, were performed to assess the diagnostic accuracy of individual miRNAs and their combined performance as panels.</p><p><strong>Results: </strong>The expression levels of miR-21, miR-29a, and miR-92a were significantly elevated in CRC patients compared to healthy controls (all <i>p</i> < 0.001). ROC analysis demonstrated that miR-92a exhibited the highest individual diagnostic performance (AUC: 0.938), followed by miR-21 (AUC: 0.907) and miR-29a (AUC: 0.898). Sensitivity and specificity were 88% and 90%, 92% and 56%, and 76% and 94%, respectively. Combinatorial analysis revealed that the miR-29a and miR-92a panel achieved the highest diagnostic accuracy (AUC: 0.976), surpassing individual miRNAs and other combinations, highlighting its potential as a robust, non-invasive biomarker panel for CRC.</p><p><strong>Conclusions: </strong>This study highlights the potential of the miR-29a and miR-92a combination, which achieved excellent diagnostic efficiency (AUC: 0.976). These findings underscore miRNA utility in enhancing early detection and reducing CRC-related mortality in Morocco.</p>","PeriodicalId":19271,"journal":{"name":"Non-Coding RNA","volume":"11 2","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11932314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chromatin Structure Around Long Non-Coding RNA (lncRNA) Genes in <i>Schistosoma mansoni</i> Gonads.","authors":"Ronaldo C Augusto, Thomas Quack, Christoph G Grevelding, Christoph Grunau","doi":"10.3390/ncrna11020025","DOIUrl":"10.3390/ncrna11020025","url":null,"abstract":"<p><p>In this study, we employed a total of eight distinct modifications of histone proteins (H3K23ac, H3K27me3, H3K36me3, H3K4me3, H3K9ac, H3K9me3, H4K12ac, and H4K20me1) to discern the various chromatin colors encompassing lncRNA genes in both mature and immature gonads of the human parasite <i>Schistosoma mansoni</i>. Our investigation revealed that these chromatin colors exhibit a tendency to aggregate based on the similarities in their metagene shapes, leading to the formation of less than six distinct clusters. Moreover, these clusters can be further grouped according to their resemblances by shape, which are co-linear with specific regions of the genes, and potentially associated with transcriptional stages.</p>","PeriodicalId":19271,"journal":{"name":"Non-Coding RNA","volume":"11 2","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11932260/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-Cell Transcriptomic Approaches for Decoding Non-Coding RNA Mechanisms in Colorectal Cancer.","authors":"Mahnoor Naseer Gondal, Hafiz Muhammad Umer Farooqi","doi":"10.3390/ncrna11020024","DOIUrl":"10.3390/ncrna11020024","url":null,"abstract":"<p><p>Non-coding RNAs (ncRNAs) play crucial roles in colorectal cancer (CRC) development and progression. Recent developments in single-cell transcriptome profiling methods have revealed surprising levels of expression variability among seemingly homogeneous cells, suggesting the existence of many more cell types than previously estimated. This review synthesizes recent advances in ncRNA research in CRC, emphasizing single-cell bioinformatics approaches for their analysis. We explore computational methods and tools used for ncRNA identification, characterization, and functional prediction in CRC, with a focus on single-cell RNA sequencing (scRNA-seq) data. The review highlights key bioinformatics strategies, including sequence-based and structure-based approaches, machine learning applications, and multi-omics data integration. We discuss how these computational techniques can be applied to analyze differential expression, perform functional enrichment, and construct regulatory networks involving ncRNAs in CRC. Additionally, we examine the role of bioinformatics in leveraging ncRNAs as diagnostic and prognostic biomarkers for CRC. We also discuss recent scRNA-seq studies revealing ncRNA heterogeneity in CRC. This review aims to provide a comprehensive overview of the current state of single-cell bioinformatics in ncRNA CRC research and outline future directions in this rapidly evolving field, emphasizing the integration of computational approaches with experimental validation to advance our understanding of ncRNA biology in CRC.</p>","PeriodicalId":19271,"journal":{"name":"Non-Coding RNA","volume":"11 2","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11932299/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Multi-Input Neural Network Model for Accurate MicroRNA Target Site Detection.","authors":"Mohammad Mohebbi, Amirhossein Manzourolajdad, Ethan Bennett, Phillip Williams","doi":"10.3390/ncrna11020023","DOIUrl":"10.3390/ncrna11020023","url":null,"abstract":"<p><p>(1) Background: MicroRNAs are non-coding RNA sequences that regulate cellular functions by targeting messenger RNAs and inhibiting protein synthesis. Identifying their target sites is vital to understanding their roles. However, it is challenging due to the high cost and time demands of experimental methods and the high false-positive rates of computational approaches. (2) Methods: We introduce a Multi-Input Neural Network (MINN) algorithm that integrates diverse biologically relevant features, including the microRNA duplex structure, substructures, minimum free energy, and base-pairing probabilities. For each feature derived from a microRNA target-site duplex, we create a corresponding image. These images are processed in parallel by the MINN algorithm, allowing it to learn a comprehensive and precise representation of the underlying biological mechanisms. (3) Results: Our method, on an experimentally validated test set, detects target sites with an AUPRC of 0.9373, Precision of 0.8725, and Recall of 0.8703 and outperforms several commonly used computational methods of microRNA target-site predictions. (4) Conclusions: Incorporating diverse biologically explainable features, such as duplex structure, substructures, their MFEs, and binding probabilities, enables our model to perform well on experimentally validated test data. These features, rather than nucleotide sequences, enhance our model to generalize beyond specific sequence contexts and perform well on sequentially distant samples.</p>","PeriodicalId":19271,"journal":{"name":"Non-Coding RNA","volume":"11 2","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11932204/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanism of Action of circRNA/miRNA Network in DLBCL.","authors":"Elena Golovina, Cory Eaton, Virginia Cox, Jozef Andel, Karina Savvulidi Vargova","doi":"10.3390/ncrna11020022","DOIUrl":"10.3390/ncrna11020022","url":null,"abstract":"<p><p>Circular RNAs (circRNAs) make up approximately 10% of the human transcriptome. CircRNAs belong to the broad group of non-coding RNAs and characteristically are formed by backsplicing into a stable circular loop. Their main role is to regulate transcription through the inhibition of miRNAs' expression, termed miRNA sponging. CircRNAs promote tumorigenesis/lymphomagenesis by competitively binding to miRNAs at miRNA binding sites. In diffuse large B-cell lymphoma (DLBCL), several circRNAs have been identified and their expression is related to both progression and response to therapy. DLBCL is the most prevalent and aggressive subtype of B-cell lymphomas and accounts for about 25% to 30% of all non-Hodgkin lymphomas. DLBCL displays great heterogeneity concerning histopathology, biology, and genetics. Patients who have relapsed or have refractory disease after first-line therapy have a very poor prognosis, demonstrating an important unmet need for new treatment options. As more circRNAs are identified in the future, we will better understand their biological roles and potential use in treating cancer, including DLBCL. For example, circAmotl1 promotes nuclear translocation of <i>MYC</i> and upregulation of translational targets of MYC, thus enhancing lymphomagenesis. Another example is circAPC, which is significantly downregulated in DLBCL and correlates with disease aggressiveness and poor prognosis. CircAPC increases expression of the host gene adenomatous polyposis coli (APC), and in doing so inactivates the canonical Wnt/β-catenin signaling and restrains DLBCL growth. MiRNAs belong to the non-coding regulatory molecules that significantly contribute to lymphomagenesis through their target mRNAs. In DLBCL, among the highly expressed miRNAs, are miR-155-5p and miR-21-5p, which regulate NF-ĸB and PI3K/AKT signaling pathways. The aim of this review is to describe the function and mechanism of regulation of circRNAs on miRNAs' expression in DLBCL. This will help us to better understand the regulatory network of circRNA/miRNA/mRNA, and to propose novel therapeutic targets to treat DLBCL.</p>","PeriodicalId":19271,"journal":{"name":"Non-Coding RNA","volume":"11 2","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11932212/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MicroRNAs: A Novel Approach for Monitoring Treatment Response in Major Depressive Disorder?","authors":"Cristina-Sorina Cătană, Monica Mihaela Marta, Daniel Ungureanu, Cătălina-Angela Crișan","doi":"10.3390/ncrna11020021","DOIUrl":"10.3390/ncrna11020021","url":null,"abstract":"<p><p>Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders, with an increasing incidence each year and an important socioeconomic burden. Although new treatments are continuously being developed, there is no effective monitoring method to determine the suitability of treatment and ensure positive outcomes. Therefore, patients often struggle with ineffective antidepressants and their potential adverse effects, which halts any future progress in managing the disorder. Considering the potential of microRNAs (miRNAs) as biomarkers for various pathologies and the increasing evidence of the modulation of several genes involved in MDD, this minireview aimed to evaluate the literature data on the impact of miRNAs in MDD and their usefulness in monitoring treatment response. The correlations between antidepressants and the expression of several miRNAs support the existence of a common epigenetic mechanism of antidepressants and explain the epigenetic differences influencing treatment efficacy in MDD.</p>","PeriodicalId":19271,"journal":{"name":"Non-Coding RNA","volume":"11 2","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11932203/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Emerging Applications of Artificial MicroRNA-Mediated Gene Silencing in Plant Biotechnology.","authors":"Luis Alberto Bravo-Vázquez, Ana Marta Castro-Pacheco, Rodrigo Pérez-Vargas, Joceline Fernanda Velázquez-Jiménez, Sujay Paul","doi":"10.3390/ncrna11020019","DOIUrl":"10.3390/ncrna11020019","url":null,"abstract":"<p><p>Improving crop yield potential is crucial to meet the increasing demands of a rapidly expanding global population in an ever-changing and challenging environment. Therefore, different technological approaches have been proposed over the last decades to accelerate plant breeding. Among them, artificial microRNAs (amiRNAs) represent an innovative tool with remarkable potential to assist plant improvement. MicroRNAs (miRNAs) are a group of endogenous, small (20-24 nucleotides), non-coding RNA molecules that play a crucial role in gene regulation. They are associated with most biological processes of a plant, including reproduction, development, cell differentiation, biotic and abiotic stress responses, metabolism, and plant architecture. In this context, amiRNAs are synthetic molecules engineered to mimic the structure and function of endogenous miRNAs, allowing for the targeted silencing of specific nucleic acids. The current review explores the diverse applications of amiRNAs in plant biology and agriculture, such as the management of infectious agents and pests, the engineering of plant metabolism, and the enhancement of plant resilience to abiotic stress. Moreover, we address future perspectives on plant amiRNA-based gene silencing strategies, highlighting the need for further research to fully comprehend the potential of this technology and to translate its scope toward the widespread adoption of amiRNA-based strategies for plant breeding.</p>","PeriodicalId":19271,"journal":{"name":"Non-Coding RNA","volume":"11 2","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11932238/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Unpaved Road of Non-Coding RNA Structure-Function Relationships: Current Knowledge, Available Methodologies, and Future Trends.","authors":"Ana Lúcia Leitão, Francisco J Enguita","doi":"10.3390/ncrna11020020","DOIUrl":"10.3390/ncrna11020020","url":null,"abstract":"<p><p>The genomes from complex eukaryotes are enriched in non-coding genes whose transcription products (non-coding RNAs) are involved in the regulation of genomic output at different levels. Non-coding RNA action is predominantly driven by sequence and structural motifs that interact with specific functional partners. Despite the exponential growth in primary RNA sequence data facilitated by next-generation sequencing studies, the availability of tridimensional RNA data is comparatively more limited. The subjacent reasons for this relative lack of information regarding RNA structure are related to the specific chemical nature of RNA molecules and the limitations of the currently available methods for structural characterization of biomolecules. In this review, we describe and analyze the different structural motifs involved in non-coding RNA function and the wet-lab and computational methods used to characterize their structure-function relationships, highlighting the current need for detailed structural studies to explore the molecular determinants of non-coding RNA function.</p>","PeriodicalId":19271,"journal":{"name":"Non-Coding RNA","volume":"11 2","pages":""},"PeriodicalIF":3.6,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11932211/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}